Evie.ai Tool for Better Workplace Environment

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Overview

The phenomenon of AI used to be a figment of science fiction authors’ imagination, yet it has established quite a firm presence in the modern reality owing to the advances made in the realm of science and engineering. As a result, the AI trend has grown to become nearly ubiquitous, with the AI-related technology currently being the driving force behind an array of processes within many industries. Defined as the attempt at recreating human intelligence, AI offers numerous opportunities in business (Weber & Schutte, 2019). In section 1, the main issue of AI in business will be addressed, including threats and opportunities. The rest of the sections will contextualize the issue as from the perspective of Evie.ai and offer recommendations.

Trends of AI

In their study, Raban and Hauptman (2018) show that the latest trends for AI in business have been predetermined by the urge to adders the problem of cybersecurity and the threat of data theft. Specifically, the study points to the urgency of developing characteristics such as cyber resilience and the creation of a blockchain within the corporate environment to reduce the external threats of cyberattacks (Raban & Hauptman, 2018). Overall, the research indicates that companies need to build the technology that can both defend and attack.

Another research that addresses the nature of AI trends and the possible opportunities for using AI as the means of forecasting and performing all kinds of analysis for business. The article by Lichtenthaler (2018) suggests that the integration of AI into business and corporate processes will lead to fewer errors and a more careful evaluation of key factors. The research creates the basis for determining how AI can be incorporated into a specific organization.

Definitions and Examples of AI for Business

In order to understand and embrace the tremendous impact that the use of AI has produced within industries and in professional performance, one will need to define the subject matter accordingly. However, remarkably enough, there seems to be little consensus on what AI is expected to mean; for example, in his research, Simon (2019) explains that AI remains an umbrella term that covers far too many types of innovations to make any conclusions concerning the nature of the concept, its impact, and its defining characteristics.

The study shows that the existing overlaps between AI and other technological innovations, such as robots, do not allow drawing a clear line between AI and other types of innovative technology. Nonetheless, the research also proves that AI has been quite effective in business, leading to a better analysis of data, forecasting of future outcomes, and defining common trends within the target industry.

Global Demands for AI

With the increase in the range of areas in which AI is applied, the global demand for the specified technology has been rising exponentially and causing it to become an important part of business processes, especially in regard to supply chain management (SCM) and the processes demanding accurate data management. The study by Weber and Schutte (2019) indicates that the importance of AI in SCM has risen extraordinarily due to the opportunities for managing Big Data and the chances to address errors that may occur during SCM-related processes (Weber & Schutte, 2019). In addition, the current demand for AI technology, in general, as the catalyst for mproving the services and patient outcomes, has risen to the total CAGR of 36.2% (“Artificial intelligence market 2019 share, trends, segmentation and forecast to 2025 | CAGR of 36.2%,” 2019).

As a result, the significance of AI has become immense for most businesses, especially in regard to retailing and the associated issues (Weber & Schutte, 2019). According to the study outcomes, the application of AI allows fulfilling orders faster and with a lesser number of errors, namely, due to the greater range of opportunities for managing logistics-related concerns.

Development of Tech Companies Globally

In addition to a better management of internal issues linked to a company’s performance in the market, technology offers the platform for constant improvement, which is why the significance of tech companies has risen globally. The research performed by Chai, Miao, Sun, Zheng, and Li (2017) proves that the significance of technology-producing organizations, as well as companies geared toward providing tech-related services and support for companies, has increased.

The described trend owes its existence to a combination of several factors, the issues of security and competition being the primary ones (Chai et al., 2017). As a result, tech companies have established themselves globally, allowing other organizations to improve their supply chains and data management.

The impact that the AI has had on organizations across the globe is truly immense. Some of the recent case studies indicate that modern organizations have expanded their supply chain extensively due to the introduction of the specified techniques into their performance strategies. For example, the Amazon Company will be remembered as one of the pioneers in applying AI to the management of its organizational processes (Incerti, 2017).

Using the AI technologies to improve the management of its stocks, the organization was one of the pioneers in utilizing AI as the basis for organizational and production-related processes within their supply chain (Incerti, 2017). Another company that deserves a mentioning as the firm that introduced AI into its environment when the technology was only emerging is Google (Li et al., 2018). Using the tool to process customer experience and queries, the AI served as the means of managing data more accurately (Li et al., 2018). Thus, the two companies in question can be chosen to represent the cases of effective application of AI technologies.

The Context (Evie.ai)

Placing the issue of technological development and the promotion of cybersecurity and SCM in a context, one will need to consider the case of Evie.ai as one of the primary examples in using AI as the tool for addressing contemporary business problems and navigating the modern business landscape effectively (Joseph, Lim, & Chun, 2018). Allowing users to interact with the interface that is tailored to their personal needs and is highly responsive, the project known as Evie.ai became a staple of a successful integration of AI-related tools in the industry.

In retrospect, the integration of Evie.ai into the range of the company’s functions and strategies can be seen as a major risk since it was considered to be a disadvantage at the time. Taking far too many resources, including not only financial ones but also the efforts of an interdisciplinary team, the time taken to implement the project, and many other issues faced during the development, Evie.ai was deemed as a liability rather than a feasible source of future income for the organization.

However, now that the product has been firmly integrated into the company’s environment, it seems to have offered several advantages, the chances to process data much faster, as well as using a much higher volume of it, being the key advantage (Joseph et al., 2018). Overall, to remain successful and keep its customers, as well as attract new ones, the company will need to consider the further evolution of Evie.ai and the ways in which it can improve the company’s performance to an even greater degree, becoming its main competitive advantage.

Business Problem

Although Evie.ai currently seems to be a model representation of an impeccable integration of an AI tool into the corporate environment, some of the aspects of its performance raise numerous questions that cannot be answered yet. The issue of corporate culture and the need to introduce culture-related modifications into the performance of Evie.ai is the main issue to be discussed, as the authors of the case specify in their assessment of Evie.ai’s productivity. Specifically, the case points to the fact that every company has a unique corporate culture that suggests a unique threshold of security and control levels, to which Evie.ai cannot adjust immediately and automatically (Joseph et al., 2018). Thus, tools for introducing manual alterations to the interface of the program are strongly needed.

In addition, Evie.ai seems to have created the environment in which employees may feel insecure about their jobs and the potential threat of Evie.ai replacing them. Along with the fear of failure that comes with the introduction o new requirements and demands for managing innovative technology, the described issue may create impediments to the implementation of the project and the management of organizational processes, namely, the issues related to information transfer and processing, within the company. The issue of resistance to change, which may occur once staff members become overly anxious about the presumed threat that Evie.ai poses to their performance within the organization has to be addressed by introducing a new leadership strategy and focusing on the needs of employees.

Problem Analysis and Challenges for Evie.ai

The current problem with Evie.ai stems from two primary areas, which are technological limitations and the positioning strategy. Recreating a genuine emotional response is currently impossible even for the most advanced AI, which suggests that Evie.ai will not be seen as the replacement of an actual assistant for customers. However, apart from the specified issue, there is another underlying concern, which is linked to how Evie.ai is positioned.

By ensuring buyers that interacting with Evie.ai will offer them a genuine experience of communication, a company is likely to set customers’ expectations far too high for them to enjoy the extent of possibilities that Evie.ai provides. Therefore, the problem with the management of Evie.ai’s popularity will also have to be addressed form a marketing perspective apart from the technological one (Joseph et al., 2018).

By using Evie.ai far too frequently, the company may create an impression of a service that intentionally distances itself form its customers, which is not the reputation that the organization should seek to obtain. Therefore, the approach toward communication with customers will have to be reconsidered, and Evie.ai will have to be rebranded as the service that links the company and its customers instead of replacing communication with its employees.

Another concern that the company will have to address s linked to the future use of Evie.ai and the expansion of its functions. By reconfiguring the extent and specifics of its functions, as well as adding new and more nuanced technology to it, the organization will be able to build the tool for performing complex financial analysis and making forecasts that will allow the organization to maintain its competitive advantage in the market that has extraordinarily high competition rates (Joseph et al., 2018). Thus, the company will benefit from the use of Evie.ai as the mediator between the organization and its customers instead of viewing it as a substitute of the actual company representative.

Finally, the issue of employment and the jobs that Evie.ai will substitute needs to be discussed. As the case study indicates, the organization has managed to convince its staff members that Evie.ai will not take their jobs away an, and that the program will never replace the people that have contributed to the company so much. However, to make sure that the rapport between the company and its employees remains stable, the organization will need to offer its employees extra benefits and incentives.

A Moreover, the staff members will need training options that will help them to gain the competencies and skills for managing the innovative technology more effectively. Furthermore, given the emergence of new responsibilities and tasks within the organization as a result of incorporating Evie.ai into it, the necessity to create new jobs and fill them has emerged. Thus, the work design will have to be rearranged, and new jobs will have to be created.

Ethical Use of AI

In addition to the problem of managing relationships between the company and its employees to maintain the levels of trust consistent and ensure that employee remain loyal to the organization, one will need to establish strong ethical standards to which every employee will have to adhere. The ethical use of AI implies that the use of Evie.ai will not pose any threat to human dignity of the participants involved, including the company’s primary stakeholders, specifically, employees and buyers, as well as indirect ones, which encompasses the members of the global community.

For this purpose, the organization will have to reinforce the efficacy of its data management and make sure that personal information of its stakeholders is encrypted and stored securely without any possibility of it being open to a third party (Wirtz et al., 2018). Thus, the extent of cybersecurity within the company will be increased.

The issue of human rights should also be addressed in regard to the possible biases within Evie.ai. Although the current record of using the software has not proven to produce any tangible harm to any of the communication participants, it will be necessary to check Evie.ai constantly for the possibility of its malfunctioning. Thus, the instances of people being misled by Evie.ai or forced into making the decisions that can potentially harm them will be prevented (Jiang, Miao, & Li, 2017).

By incorporating Evie.ai into the set of digital tools used for communication with buyers, the firm accepts hug e moral and ethical responsibility, which it needs to take with due seriousness. Thus, at present, Evie.ai seems to hold a lot of potential, especially in regard to the analysis of the Big Data and the management of a vast amount of information (Mascarenhas, 2018). However, as far as its use as the medium between the company and its clients is concerned, it should not be viewed as the substitute for the actual live communication with the organization’s members. Instead, Evie.ai should be improved to include other functions such as the opportunity for calculating financial risks and opportunities that the company faces in the target market.

Conclusion

Given the inclusion of a new tool into the workplace process, namely, the integration of Evie.ai into the organizational performance, strategies for monitoring its efficacy, controlling it, and maintaining the service consistently efficient will be required. Therefore, the main focus of the new jobs will include technical maintenance, development, and control functions. Thus, corresponding training opportunities will have to be offered to staff members (Nikitin, Nemov, & Prokofiev, 2016).

Currently, the chances for turning Evie.ai into the competitive advantage of the organization and using it to propel the firm to the top of its industry can be possible. Given the rise in the global demand for AI, the focus on expanding the opportunities that Evie.ai provides and using it to collect financial data, as well as perform its analysis and provide future forecasts, should be deemed as crucial (Khalyasmaa & Eroshenko, 2017).

Moreover, the organization will have to use Evie.ai as the tool for reestablishing the principles of corporate loyalty, improving communication within the firm, and addressing the needs of staff members.The inclusion of Evie.ai into the company’s supply chain and especially using it to create a blockchain framework within which the organization will expand to establish a global presence should also be deemed as an important goal (Zuev et al., 2016).

Even though the firm cannot be considered as having a huge competitive advantage compared to other organizations working in the same field, the expansion of Evie.ai and its use in the SCM processes will help to create more accurate forecasts, minimize the impact of risks, and address the threat of miscommunication between stakeholders. Therefore, as the tool for enhancing work, Evie.ai holds a massive potential and needs to be expanded to improve the workplace environment for employees, as well as create extra opportunities for the firm to succeed in the global market.

References

Artificial intelligence market 2019 share, trends, segmentation and forecast to 2025 | CAGR of 36.2%. (2019). Web.

Chai, Y., Miao, C., Sun, B., Zheng, Y., & Li, Q. (2017). Crowd science and engineering: Concept and research framework. International Journal of Crowd Science, 1(1), 2–8. Web.

Incerti, F. (2017). Amazon Echo: Emerging technology for formal or informal learning? In Society for Information Technology & Teacher Education International Conference (pp. 1627-1633). New Orleans, LA: Association for the Advancement of Computing in Education (AACE).

Jiang, Z., Miao, C., & Li, X. (2017). Application of keyword extraction on MOOC resources. International Journal of Crowd Science, 1(1), 48–70. Web.

Joseph, D., Lim, W. K., & Chun, C. T. (2018). Evie.ai: The rise of artificial intelligence, and the future of work. HBS No. NTU226. Boston, MA: Harvard Business School Publishing.

Khalyasmaa, I. A., & Eroshenko, S. A. (2017). The analysis of efficiency of artificial intelligence methods application for an assessment of feasibility of scientific and technical decisions. 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM) (pp. 883-886). Piscataway, NJ: IEEE. Web.

Li, L., Lin, Y. L., Zheng, N. N., Wang, F. Y., Liu, Y., Cao, D.,… Huang, W. L. (2018). Artificial intelligence test: a case study of intelligent vehicles. Artificial Intelligence Review, 50(3), 441-465. Web.

Lichtenthaler, U. (2018). Beyond artificial intelligence: why companies need to go the extra step. Journal of Business Strategy. Web.

Mascarenhas, SJ, F. O. A. (2018). Artificial intelligence and the emergent turbulent markets: New challenges to corporate ethics today. In Corporate Ethics for turbulent markets: The market context of executive decisions (pp. 215-242). Bingley, UK: Emerald Publishing Limited.

Nikitin, A. V., Nemov, D. A., & Prokofiev, S. V. (2016). A distributed subsystem for design decisions optimization in the framework of organizational approach. In 2016 XIX IEEE International Conference on Soft Computing and Measurements (SCM) (pp. 127-128). Piscataway, NJ: IEEE.

Raban, Y., & Hauptman, A. (2018). Foresight of cyber security threat drivers and affecting technologies. Foresight, 20(4), 353–363. Web.

Simon, J. P. (2019). Artificial intelligence: Scope, players, markets and geography. Digital Policy, Regulation and Governance, 21(3), 208–237. Web.

Weber, F. D., & Schutte, R. (2019). State-of-the-art and adoption of artificial intelligence in retailing. Digital Policy, Regulation and Governance, 21(3), 264–279. Web.

Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave new world: Service robots in the frontline. Journal of Service Management, 29(5), 907-931. Web.

Zuev, D. V., Garbaruk, V. V., Khodakovsky, V. A., Fedorchuk, P. E., Blagoveshchenskaya, E. A., & Kunets, D. S. (2016). On neural network online learning algorithm. In 2016 XIX IEEE International Conference on Soft Computing and Measurements (SCM) (pp. 279-280). Piscataway, NJ: IEEE.

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